This tool enables in-database scoring of 'XGBoost' models built in R, by translating trained model objects into SQL query. 'XGBoost' <https://xgboost.readthedocs.io/en/latest/index.html> provides parallel tree boosting (also known as gradient boosting machine, or GBM) algorithms in a highly efficient, flexible and portable way. GBM algorithm is introduced by Friedman (2001) <doi:10.1214/aos/1013203451>, and more details on 'XGBoost' can be found in Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>.
|Author||Chengjun Hou [aut, cre], Abhishek Bishoyi [aut]|
|Maintainer||Chengjun Hou <[email protected]>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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